The motor unit is the fundamental element of motor output and consists of a motoneuron and the muscle fibers that its axon innervates. Muscle fiber twitches are normally 1-to-1 with motoneuron action potentials and thus the motor unit is a single functional entity. Despite this, most studies, both experimental and simulation, tend to focus either on motoneurons or on muscle. This separation of focus has sharply limited understanding of motor outflow in both normal and pathological states. To bridge this gap, this proposal seeks to develop a highly realistic and thoroughly validated computer simulation of the set of motor units for a single muscle. We focus on hindlimb extensors in the cat, for which the most complete experimental database is available. The key issue limiting previous efforts at simulating motor units is the lack of understanding of the effects of neuromodulators on conversion of synaptic input to spiking outputs in motoneurons. Systematic studies in our lab and many others have now identified these neuromodulator effects, and found them to be remarkably strong in influencing motoneuron excitability. The most potent of all are serotonin (5HT) and norepinephrine (NE), which are released in the spinal cord by axons originating in the brainstem. 5HT and NE facilitate persistent inward currents (PICs) in the dendrites of motoneurons, which then amplify synaptic input by as much as 5-fold. We have successfully developed an initial model of the motoneuron with PICs. Moreover, we have successfully developed a good muscle model for representing muscle units. In Aim 1 of the proposed work, these initial models are further developed, carefully validated against experimental data and expanded into the set of more the 200 members needed to accurately represent the full motor pool and muscle. In Aim 2, we use the simulated pool/muscle to investigate the structure of motor outflow, focusing on how neuromodulatory inputs alter overall system gain as well as influence details like motoneuron firing patterns and noise fluctuations in force. This model has great potential for use in a wide range of simulations of motor control, but simulations that involved multiple sets of neurons and multiple muscles require computational efficiency. Thus in Aim 3, we investigate several different approaches for simplifying the full set of 100s of motor units to achieve great increases in computational speed. Successful completion of these aims will provide a biologically realistic model of motor output that can be used in a wide range of computational studies of the neural control of movement. These simulations can be used to generate deep insights into the structures of motor commands and to identify deficits in motor systems in disease states like spinal injury. In the long term, we hope to develop a user interface to allow widespread use by the motor control community.